This post is adapted from a longer, more wide-ranging post on Substack where I attempt to collect some of my thoughts about AI as a relative outsider to the field. The section I have decided to share here, though, I believe to be novel.

Success in self-play by game AIs like AlphaZero has led to some interest in its possibility of loosening (or even doing away with) the data bottleneck that threatens to strangle scaling as a path forward for LLMs. By making analogies to the human phenomena of dialects and group polarization, I provide a starting point for further, more analytically-framed arguments against self-play as a viable future for increasing the intelligence or linguistic capacity of LLMs.

The Viability of the Analogy

My argument rests, crucially, on an analogy between an AI using self-play to create its own training data and a human (or group of humans) interacting with each or the world to learn and adapt. I believe this is a defensible analogy.

Self-play is quite easy to translate into human cognitive experience. What defines self-play is that the same neural network which creates the new data is also the one which learns by it. The fact that this is possible might be philosophically interesting, but the actual experience is pedestrian.

When a chess player computes his next moves — “I do that, then she does that, I take there, she takes back, I move there, check, check, take, take… no, not good” — the chess player is doing a sort of self-play. Even more direct of an analogy is the fact that chess players often do play themselves in chess, and can learn from that experience. The fact that this is fairly directly analogous to AI self-play seems to me obvious.

What may be less obvious but also seems true to me is that self-play is functionally equivalent as well to a siloed group of functionally equivalent human individuals acting amongst one another. The important part is that they are siloed, that they only have the background conditions of cognition and the game itself to go off of. Given enough time and communication, knowledge becomes communal, and we can consider the group as a single intelligence. Or, if that doesn't seem right, we can pluck one person from the group and expect them to have similar behavior as anyone else in the group.

What is important for this analogy is that it is not surprising that AlphaZero was able to learn better chess than an...

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